Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180332PMC
http://dx.doi.org/10.1017/ice.2020.119DOI Listing

Publication Analysis

Top Keywords

application effects
4
effects fever
4
fever screening
4
screening system
4
system prevention
4
prevention nosocomial
4
nosocomial infection
4
infection designated
4
designated hospital
4
hospital coronavirus
4

Similar Publications

Developing of molecular crystalline materials with light-induced multiple dynamic deformation in space dimension and photochromism on time scales has attracted much attention for its potential applications in actuators, sensoring and information storage. Nevertheless, organic crystals capable of both photoinduced dynamic effects and static color change are rare, particularly for multi-component cocrystals system. In this study, we first report the construction of charge transfer co-crystals allows their light-induced solid-to-liquid transition and photochromic behaviors to be controlled by trans-stilbene (TSB) as an electron donor and 3,4,5,6-Tetrafluorophthalonitrile (TFP) as an electron acceptor.

View Article and Find Full Text PDF

Endophytes have significant prospects for applications beyond their existing utilization in agriculture and the natural sciences. They form an endosymbiotic relationship with plants by colonizing the root tissues without detrimental effects. These endophytes comprise several microorganisms, including bacteria and fungi.

View Article and Find Full Text PDF

Systematic Review of Hybrid Vision Transformer Architectures for Radiological Image Analysis.

J Imaging Inform Med

January 2025

School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.

Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.

View Article and Find Full Text PDF

Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.

View Article and Find Full Text PDF

Background: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in such treatments.

Purpose: This study seeks to address this gap by developing a DL model for independent MC dose (MCDose) prediction, aiming to facilitate OART and rapid QA implementation for HIT.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!